Monetizing Data With AI: MIT CISR's Barb Wixom

**Shervin Khodabandeh** (0:02)
What's the most important way to measure the impact of AI on an organization's success? One AI researcher shares her opinion on today's episode.

**Barbara Wixom** (0:13)
I'm Barb Wixom from MIT Cisr, and you're listening to Me, Myself, and AI.

**Sam Ransbotham** (0:19)
Welcome to Me, Myself, and AI, a podcast on artificial intelligence in business. Each episode, we introduce you to someone innovating with AI. I'm Sam Ransbotham, Professor of Analytics at Boston College. I'm also the AI and Business Strategy Guest Editor at MIT Sloan Management Review.

**Shervin Khodabandeh** (0:38)
And I'm Shervin Khodabandeh, Senior Partner with BCG and one of the leaders of our AI business. Together, MIT Smr and BCG have been researching and publishing on AI since 2017, interviewing hundreds of practitioners and surveying thousands of companies on what it takes to build and to deploy and scale AI capabilities and really transform the way organizations operate.

**Sam Ransbotham** (1:05)
Hi, listeners. Thanks for joining us. Shervin and I are talking today with Barb Wixom. She's a Principal Research Scientist at MIT's Center for Information Systems Research, known as CISR. Barb's been leading research on technology topics at CISR since 2013 and has new research on the use of data in AI and business. As listeners know, Shervin and I have both been researching similar topics for years as well now, and we kind of feel like Barb is a kindred spirit in that respect. So we're hoping to talk about some of our shared experiences and perhaps get a little bit nerdy about researching about AI in general. It's a really fast-moving complex topic that it's kind of hard to understand well. And just as an aside, Barb is one of my favorite people in academia. Oh, actually, why did I even qualify that with in academia? That was dumb of me. I should have Barb is one of my favorite people. So first of all, welcome to Me, Myself, and AI.

**Barbara Wixom** (1:59)
Oh, my goodness. Thank you, Sam. And thank you for such a kind introduction.

**Sam Ransbotham** (2:03)
Let's start, Barb, with you giving our listeners a better idea of what your role at Cisr is, what Cisr does, and I gave a cursory overview. Give us some depth.

**Barbara Wixom** (2:13)
Well, it's pretty fun. Cisr just celebrated its 50th anniversary at MIT. In fact, we had the founder, Just Give a Talk, Scott Morton. He came out of a Harvard PhD back in the 60s, early 60s, and he has the honor of being the very first doctoral dissertation in the area of decision support. In fact, he told a really funny story where he pitched as his doctoral topic, the idea of taking data out of a system and using it for management information, basically. He was trying to optimize laundering machines at the time, and his advisor said that was the stupidest thing he had ever heard. Why would we ever waste computing power using data from systems in order to inform decision-making?

**SPEAKER_4** (3:03)
That didn't age very well.

**Barbara Wixom** (3:05)
No, it did not. Fortunately, he switched advisors, proved his first advisor wrong, and literally started the field of decision support. So when he earned his degree, he became a faculty member of MIT, and he started the Center for IAS Research in 1974 This is before we had CIOs and large organizations were struggling with managing tech and succeeding in tech. And so Cisr was established to help leaders succeed. It's actually a nonprofit. And we still do that today. We still help leaders succeed with technology. And my role is to help specifically with data. And of course, now, well, it's always been AI as well. And we can talk about how I see the two of those animals.

**Shervin Khodabandeh** (3:51)
Barb, how does your role specifically work on helping leaders succeed? I'd imagine it's through research and maybe coaching. But can you share some more specific examples?

**Barbara Wixom** (4:01)
I have a book called Data Is Everybody's Business that just came out fall of 2023 And the book was a synthesis of literally 30 years of my research. So I started researching in the space of data warehousing, which again, back then also included advanced analytics, which we now would categorize as AI in 1994 And what we found today is there's such a pervasive need across an organization, everybody from a frontline worker all the way up to a board member, to understand how to think about data and AI in productive ways. And so that's what the book is. Well, as you can imagine, data is everybody's business. The first question is, well, how does AI figure in? And so what I've been recently doing is a lot of work to inform how AI fits into data. Because I, and we can debate this, I passionately believe that AI is not something you should pursue outside the context of data monetization. And I know we're going to have to pause and define this first, because there are too many listeners out there thinking data monetization, isn't that selling people data in creepy ways? No, no, that is not how I believe we should be thinking about data monetization. Data monetization is when you start with data as an organizational resource, and you end up with money and economic resource, and there's a conversion that happens in the organization. AI is a technology that helps in that conversion process.